agent-native-architecture

Agent-native architecture treats software agents as first-class workers that orchestrate outcomes through atomic tools and prompts. Agents reason in loops, using dynamic context injection and a shared workspace to coordinate end-to-end workflows.

You build emergent capability by defining a living system prompt, a set of atomic tools, and a context.md file for accumulated knowledge. New capabilities are created by composability, where prompts orchestrate primitive tools into complex outcomes.

Agent-native architecture is framework-agnostic but supports MCP tool integration. It requires a living system prompt, atomic tools, context.md for knowledge accumulation, and governance checks for parity, testing, and safety to ensure resilient autonomous workflows.

You ensure parity by applying governance checks that map UI actions directly to agent capabilities. This parity principle guarantees that features are outcomes of primitive tools, maintaining resilience and consistency across end-to-end workflows.

Agents improve over time through accumulated context and refined prompts. A shared workspace pattern and context.md file capture accumulated knowledge, allowing the living system prompt to dynamically adjust behavior and enhance emergent capabilities.

You should avoid agent-native architecture if your system lacks clear governance checks for parity, testing, and safety. Without a living system prompt and dynamic context injection, atomic tools cannot safely compose into emergent capabilities or reliable workflows.